发表机构
School of Computer Science, Northwestern Polytechnical University（西北工业大学计算机科学学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对大视角无人机到卫星地理定位难题，提出OffNadirLoc基准及ONLoc框架，采用结构感知加权和视图一致学习策略，实验证明该方法性能优于现有技术，且具强零样本泛化能力。
AI 中文摘要
无人机与卫星图像之间的跨视角地理定位仍然是一项基本但极具挑战性的任务，尤其是在大视角情况下会出现严重的透视失真、遮挡和外观差异。现有基准和方法主要关注近视角场景，忽视了结构场景理解和域内关系约束的重要性。本文引入了OffNadirLoc这一大视角无人机到卫星地理定位的新基准。提出了ONLoc框架，采用结构感知上下文加权机制强调可靠局部特征，抑制模糊或重复区域。设计了视图一致学习策略，将卫星图像和多视角无人机图像视为语义组进行集级监督，使模型学习视角不变且有判别力的特征。在OffNadirLoc基准和四个近视角数据集上的实验表明，该方法优于现有方法，且对未见数据集有强零样本泛化能力。代码将在指定网址发布。
英文摘要
Cross-view geo-localization between UAV and satellite imagery remains a fundamental yet highly challenging task, especially under large off-nadir views where drastic perspective distortions, occlusions, and appearance gaps occur. Existing benchmarks and methods primarily focus on near-nadir scenarios and often overlook the importance of structural scene understanding and intra-domain relational constraints, limiting their performance in real-world deployments. In this work, we introduce OffNadirLoc, a new benchmark for large off-nadir UAV-to-satellite geo-localization. To tackle the unique challenges posed by off-nadir perspectives, we further propose ONLoc, a framework that incorporates a structure-aware contextual weighting mechanism to dynamically emphasize reliable local features while suppressing ambiguous or repetitive regions. Additionally, we design a view-coherent learning strategy, which treats one satellite image and the corresponding UAV images from multiple views as a cohesive semantic group. This set-level supervision enables the model to learn viewpoint-invariant and discriminative features, making it more effective at capturing multi-view consistency than conventional pairwise contrastive learning. Extensive experiments on the OffNadirLoc benchmark and four near-nadir datasets demonstrate that our method consistently outperforms state-of-the-art approaches while exhibiting strong zero-shot generalization to unseen datasets without additional training. The code will be released at https://montalario.github.io/offnadirloc/.
